ESQ wrote:Compare that to something like coaches rating a player's game out of 5 using only their subjective opinion, and its no surprise Tippett has been so successful.

This "rating players out of five" thing, I've seen people use it in a vaguely pejorative sense a few times.. and rightly so given the subjectivity inherent in it. The only place I've seen it was in the first 24/7 series, with Dan Bylsma and Ray Shero using it to grade each player's performance the previous game.

Are there other coaches on record using it?

If not, it's hard to argue with the success Bylsma has had particularly considering all the injuries in Pittsburgh over the last two seasons.. perhaps they've improved their methods or perhaps they were already using more reliable methods and simply chose not to use them on camera..

I read somewhere the "out of five" rating system was shown to overvalue the bottom half of a coach's roster. It was believed to be a result of the coach expecting a little less out of his bottom half, so he rates them higher for reaching a lower bar.

Larry Goodenough wrote:I read somewhere the "out of five" rating system was shown to overvalue the bottom half of a coach's roster. It was believed to be a result of the coach expecting a little less out of his bottom half, so he rates them higher for reaching a lower bar.

That's what I recall too, I haven't been able to find that article though.

If you do it please post, I'd like to read it. Not that the point put forward doesn't make perfect sense.. I'd be awfully hard not to give Dale Weise 3/5 for playing nine minutes against scrubs with nothing good (or bad) to show for it but if Daniel Sedin had a game like that they'd be howling in the press, talk radio, message boards, etc.. about what a poor performance it was.

Does Sami Pahlsson read well on Advanced stats/Moneypuck? Cause I am somewhat baffled as to why the Shut Down Specialist has been a minus player 11 out of his 12 NHL seasons? Strange eh? I would say it has something to do with the fact that he has only netted double digit goals once in all of those 12 seasons, 11 goals is his career high, about double his average. The rest of the 11 seasons he has only netted single digit goals.

"I just want to say one word to you. Just one word. Are you listening? - Plastics." - The Graduate

RoyalDude wrote:Does Sami Pahlsson read well on Advanced stats/Moneypuck? Cause I am somewhat baffled as to why the Shut Down Specialist has been a minus player 11 out of his 12 NHL seasons? Strange eh? I would say it has something to do with the fact that he has only netted double digit goals once in all of those 12 seasons, 11 goals is his career high, about double his average. The rest of the 11 seasons he has only netted single digit goals.

Plus/minus is considered a dinosaur stat amongst advanced stat analysts - it has been proven to be more of a reflection of goaltending and shooting percentages than play.

Pahlsson does lead all Vancouver players in Corsi relative to quality of competition numbers. He also takes less than 30% of his faceoffs in the offensive zone. What that means is he plays tough minutes against top opposition and still drives the play forward.

Since Pahlsson joined Vancouver, the team's scored tied fenwick % went from 49% to 57.5%. That's a jump from mid-pack to top of the league in the advance stat that has been proven to most accurately prove the quaity of a team. I'll also add this improvement came while the team appeared uninterested due to 2nd place being locked down.

That fenwick improvement appears to be a combo of adding Pahlsson and removing Hodgson

I read, since Hodgson went to Buffalo, his score tied fenwick % is 37%. He is getting dominated at even strength with the puck flying at his own goal twice as often as at the opponents goal when he's on the ice.

donlever wrote:Nope, but you're wasting your time stating facts in this particular instance.

Although you probably know that laready.

And right after I wrote the above, I found Cam Charron's blog, outlining Vancouver's advanced stats since the trade deadline. I think adding Pahlsson over Hodgson has something to do with these good numbers.

The thing to feel good about is the very low shooting percentage since the deadline. Shooting percentages always regress to the norm. So the question should not be "Can the Canucks score enough", it should be "when will the canucks start scoring again."

-I looked back at scoring chances, and Vancouver have done an incredible job at working those. Over the last 11 games since the deadline, with the score-tied at even strength, Vancouver has earned 78 scoring chances to opponents’ 56. That’s a 58.2% rate, so not only is Vancouver keeping the puck in the other teams’ end, they are also getting quality opportunities.

-The problem with the Canucks is that they are shooting just 5.5% ( goals / total shots on goal ) in that span, well below their average of about 8.5-9%. Oddly enough, it’s been the goaltending that’s been holding up, with the team getting .942 even strength goaltending in score-tied situations, 7 goals against off of 120 shots.

-Even strength totals for Vancouver have the team shooting just 4.9% over the course of the last 11 games. That has been the issue. The goaltending has been right where you’d expect it to be with two good goaltenders (.925) but for all the talk about killer instinct and not putting opponents away, it’s really been that shooting percentage that’s killed the Canucks. That’s completely factoring out how unlucky their powerplay has been, too, but that will come around.

-Despite the Canucks outshooting their opponents 94-56 with him on the ice, Alex Burrows is a minus-2. Plus/minus statistics mean very little and ought to be disregarded, especially over small samples, for this very reason.

That is awesome work....so If I read these figures and understand them correctly.....we are in a bit of a scoring slump that should turnaround naturally if we keep playing similarly.Nice to have backup stats..

Finally, I decided to play along and check plus minus numbers for top defensive players from the past.

Bob Gainey is often considered the greatest defensive player ever. While playing for the dynasty Canadiens in the 77-79 years (years in which parody was non-existant), his plus minus was Plus 11, plus 11 and minus 2.

Guy Carbonneau was the other who came to mind. The year he won the Cup with Dallas as their shutdown guy, he scored 4 goals and was minus 3.

The thing about shutdown specialists and their poor +/-, is that they normally play against the opposing teams' best players, and thus even when they do a good job often will end up with negative numbers.

I spend several hours a day working with databases and using stats to identify trends and detect anomalies in 2D, 3D and at times 4D and 5D. I would not call myself a statistician, but I can work with numbers fairly well. I have also long been a fan of the work Bill James has done with baseball numbers. I still have copies of his annual Baseball Abstract from the early eighties sitting on my bookshelf.

Bill's greatest achievement was demonstrating the correlation between minor and major league performance and then using minor league stats to accurately project major league performance. One paper he wrote on projecting team performance based upon number of players having career years the previous season is a work of art.

I am quite skeptical when I see people throwing numbers around. There are a few simple things to note when you work with stats. Cam Charon's (sic?) chances for/against model is an exceptional example of how not to compile stats.

First is data verification. Are the numbers collected any good, how were they collected and what biases are there in the data collection? Do some simple stats of mean and standard deviation plots to see variability in the data. This will highlight variability in the data and give an indication how useful it is. If you have highly variable data, you quite likely have too small of a sample size and you should use a +/- factor (commonly 2 standard deviations) when working with the numbers. Of note is that this +/- factor accumulates when you perform calculations with the stats and can become significantly large, even larger than the represented stat value, very quickly.

Second, look at correlation coefficients to identify data linkages. I looked at Cam's data wel Spud linked to it early in the season and saw that chances for had a direct correlation to TOI. What as interesting, was that chances against did not correlate to TOI. At that point it was obvious that Cody was playing sheltered minutes.

Another problem In the case of the chances for/against model, the obvious problem was the home plate area for defining chances. Point shots and even shots from the deep slot would not count. Another issue would be the definition of a shot. I could not find one on the blog. Is it a shot on net or a shot directed at the net? i would hope they using shots directed at the net, but how are say passes to a player ion the backdoor with a yawning cage that are either tipped or fanned on dealt with in the data collection?

I also noted that at that point in the season, the data was subject to a fair bit of variability. I recall the Sedins had had games with about 3 chances and other games with 10-13 chances. Without the raw data it is impossible to calculate means and standard deviations. That wide variability would lead to a high 2nd standard deviation. When they chose to represent the chances for/against as a percentage they should have given it a +/- of three times the 2nd standard deviation. That amount could be a very significant figure and throw much of the derived results into question. I was quite conceivable to see a player have a %Chances for/against value of 67% +/-12%. When team is in a group with a range of 30% between highest and lowest, that +/-12% is huge.

I suspect that teams use a GIS system to track scoring attempts. For an investment of a few tens of thousands of dollars a system could be adopted that would allow touch screen input of the location on the ice of the origin of the shot/pass and then input of what happened to the shot/pass. Was it tipped/deflected/fanned on/blocked. Was it a goal/save/post/wide (and by how much)/rebound.

We use similar systems for our field mapping and data collection, simplistic systems are available as phone apps.

Using such a system, the pass to create a chance that someone mentioned Tippet uses could be easily tracked.

Nothing too different than what is done for charting shooting tendencies or goaltenders save/weakness tendencies, just adding some additional detail.

I read with amusement when the folks who came up with the Chances for/against blog used the movie Money Ball as a validation of their work. When I watched the movie I thought it was more a condemnation of there simplistic approach. Tellingly there is a scene where the fat fuck is charting pitches in a strike zone displayed on his computer. The shot shows multicoloured dots representing balls, strikes, curve balls, fast balls and whatever, and serves to highlight how overly simplistic Cam's work is.

It is funny watching people use these stats to justify were a team is in the here and now, the true power of these advanced stats was shown by Bill James in projecting a players value in the future.

Corsi is an interesting beast and appears to steal heavily from the work done in tracking bowler and batter stats for cricket rankings. In that work, not only is strength of opponent tracked, but also the difficulty of the cricket ground being played on.The stats also carry a weighting based upon time, with most recent performance given more credence than past work. This gives a very useful trend line to a players performance.